Yuchen Zhu 朱雨宸

Machine Learning PhD @ Georgia Tech 🍀

prof_pic.jpg

Photo credit to Sichen. Grand Canyon.

Hi, I am Yuchen Zhu, a 3rd year Machine Learning PhD at Georgia Tech, advised by Molei Tao and Yongxin Chen.

I work on generative AI. My current research centers on building the next generation of LLMs with greater efficiency and capability, through the development of diffusion language models (dLLM). I study RL-based post-training, inference-time scaling, and distillation for dLLMs. I also work on diffusion models and their multimodal variants for vision and language.

I am currently a Research Scientist Intern at Adobe Research, working on building capable dLLM.

I graduated wutg BS in Mathematics (Honors) from NYU Shanghai and MA in Statistics from Yale University. My research started in applied mathematics, optimal control and RL theory, and has since evolved toward generative AI.

You can find more details in my CV here.

📧 Feel free to reach out: yzhu738@gatech.edu / yuchenzhu0226@gmail.com

Updates

Selected Publications

  1. rethinking-rl-diffusion.png
    Rethinking the Design Space of Reinforcement Learning for Diffusion Models: On the Importance of Likelihood Estimation Beyond Loss Design
    Jaemoo Choi*, Yuchen Zhu*, Wei Guo, Petr Molodyk, Bo Yuan, Jinbin Bai, Yi Xin, Molei Tao, and Yongxin Chen
    Preprint, 2026
    rl · diffusion
  2. dmpo.png
    Enhancing Reasoning for Diffusion LLMs via Distribution Matching Policy Optimization
    Yuchen Zhu*, Wei Guo*, Jaemoo Choi, Petr Molodyk, Bo Yuan, Molei Tao, and Yongxin Chen
    Preprint, 2025
    rl · dllm
  3. mdns.png
    MDNS: Masked Diffusion Neural Sampler via Stochastic Optimal Control
    Yuchen Zhu*, Wei Guo*, Jaemoo Choi, Guan-Horng Liu, Yongxin Chen, and Molei Tao
    NeurIPS 2025
    sampling · rl · dllm
  4. tr2d2.png
    TR2-D2: Tree Search Guided Trajectory-Aware Fine-Tuning for Discrete Diffusion
    Sophia Tang*, Yuchen Zhu*, Molei Tao, and Pranam Chatterjee
    Preprint, 2025
    rl · dllm · bio
  5. fast-solver.png
    Fast Solvers for Discrete Diffusion Models: Theory and Applications of High-Order Algorithms
    Yinuo Ren*, Haoxuan Chen*, Yuchen Zhu*, Wei Guo*, Yongxin Chen, Grant M Rotskoff, Molei Tao, and Lexing Ying
    NeurIPS 2025
    dllm · inference
  6. diffuse-everything.jpg
    Diffuse Everything: Multimodal Diffusion Models on Arbitrary State Spaces
    Kevin Rojas*, Yuchen Zhu*, Sichen Zhu, Felix Ye, and Molei Tao
    ICML 2025
    diffusion · dllm · multimodal
  7. diffusion-gene-expression.png
    Diffusion Generative Modeling for Spatially Resolved Gene Expression Inference from Histology Images
    Sichen Zhu*, Yuchen Zhu*, Molei Tao, and Peng Qiu
    ICLR 2025
    diffusion · bio

Talks

  • 03/2026 INFORMS Optimization Society Conference 2026
  • 09/2025 GT ML Student Conference
  • 08/2025 MolSS Reading Group
  • 11/2024 GT ML Student Seminar
  • 10/2024 SIAM MDS 2024
  • 04/2024 Southeast ACM Student Workshop 2024